genDispatch

Power plant dispatch model, including the energy product-only model of NEMS

1 Setup

Copy all the files and directories (as they are) in your desired project location (just make sure you have write access to). genDispatch was built with Python 3.7 and

• NumPy 1.16.5
• SciPy 1.3.1
• Pandas 0.25.1
• Matplotlib 3.1.1
• Pint 0.9 (expicit units)
• FuzzyWuzzy 0.17.0 (string matching)
• xlrd 1.2.0

2 Project directory

The project directory is structured as follows:

• top level contains all source codes
• Inputs and resources contains the input files and low-level resources, such as:
  • config.ini is the configuration file, which defines project-level parameters
  • Pint energy defn.txt is a custom Pint 0.9 units definitions file
  • metadata.ini contains metadata and instructions to read the inputs data (parsed via DataHandler.py)
  • genDispatch.log is the project log
  • SG power plant database v3.xlsx is the power plant database file. This, as with many other inputs, can be configured via the metadata file.
• Results contains all the dispatch-related results
• To WRF contains all the WRF input files and resources
• Scripts contains demos and auxiliary scripts (Jupyter notebooks)

3 Scripts

i) Minimal example and walkthrough.ipynb

This ntbk shows how to simulate a full scenario and how to process the dispatch results into WRF input files.

ii) Create WRF files from saved results.ipynb

After simulating scenarios, we might want to save the dispatch results first, before transforming these into WRF inputs. This notebook demonstrates how to read saved results and then transform them.

To save the results, simply pickle the results returned by genDispatch.solve(). ToWRF.read_results() lets you pick these results up.

iii) genDispatch config writer.ipynb, genDispatch metadata writer.ipynb

These are auxiliary scripts that let you conveniently edit the config and metadata files, respectively.

Credits

Author: David Kayanan
Contact: [email protected]
Project: Cooling Singapore 1.5